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== Co-/contra- variance of 'vectors' (per se) or of their components ==
== Notation burdened with crap. ==
It is my understanding that a vector, per se (i.e. not its representation), is neither covariant or contravariant. Instead covariance or contravariance refers to a given representation of the vector, depending on the basis being used. For example, one can write the same vector in either manner as, <math>\vec{A} = a^i e_i = a_i e^i</math>. I think this point (in addition to the variance topic as a whole) can be both subtle and confusing to people first learning these topics, and thus the terminology should be used very carefully, consistently, and rigorously. I tried to change some of the terminology in the article to say, "vectors with covariant components" instead of "covariant vectors" (for example), but this has been reversed as inaccurate. So I wanted to open a discussion in case I am mistaken or others disagree. @JRSpriggs. [[User:Zhermes|Zhermes]] ([[User talk:Zhermes|talk]]) 16:45, 2 January 2020 (UTC)
Definition section would benefit hugely from being written with some sort of coherent standard of notation. I think we are probably allowed to assume that the reader knows what a linear transformation, basis, and coordinate vector with respect to a basis are, or certainly is capable of clicking links. There's no need to be summing over indices in both superscripts and subscripts and what the hell is this needless reference to the basis in brackets doing anyway? <small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[Special:Contributions/50.141.31.25|50.141.31.25]] ([[User talk:50.141.31.25|talk]]) 21:47, 19 November 2015 (UTC)</small><!-- Template:Unsigned IP --> <!--Autosigned by SineBot-->


:I have several textbooks that describe ''covariance'' and ''contravariance'' of tensors. Most of them refer to the tensors themselves as having these properties; however, some of them indicate that these properties apply only to the components and that the tensors are ''invariant''. I am inclined to agree with the latter, that is, that only the components change—not the tensors. I think we should point out in the article two things: 1. what we think is the correct parlance, and 2. the fact that some textbooks say otherwise. I can supply citations.—[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 17:54, 2 January 2020 (UTC)
:1. I don't see any place the notation is incoherent. The components of a vector depend on the choice of basis, and the notation indicates clearly shows the basis. This dependence is appropriately emphasized throughout the section ("coherently"). In fact, I would say that the whole definition section is scrupulously coherent. A transformation of the basis is also shown clearly in the notation, and it is easy to show how this changes the vector and covector. Another way to indicate this dependence is using parentheses as opposed to square brackets (see, for example, Raymond Wells, ''Differential analysis on complex manifolds''), with subscripts (e.g., Kobayashi and Nomizu, ''Foundations of differential geometry''), or just with some ad hoc method (like "Let <math>v^i</math> be the components of ''v'' in the basis '''f''', and <math>\tilde{v}^i</math> be the components of ''v'' in the basis <math>\tilde{\mathbf{f}}</math>"). It seems here better to use a notation where the dependence on the basis is explicitly emphasized, because that's what the article is really about.
:2. "I think we are probably allowed to assume that the reader knows what a linear transformation, basis, and coordinate vector with respect to a basis are, or certainly is capable of clicking links." I agree with this, which is why the article doesn't define these things, except to write them down and fix the notation as it's used in the article, which is just a best practice for writing clear mathematics and not intended to be a substitute for knowledge that can be gleaned from clicking links. Also, linear transformations are not even mentioned until the very last section of the article. And the article doesn't define those either.
:3. As for why the [[Einstein summation convention]] is not used in the definition section, it seems likely that some readers of the article will not have seen it before. It does no harm to include the summation sign. It's not like we are going to run out of ink, or expressions are going to become tangled messes of indices there. Covariance and contravariance should arguably be understood ''before'' the Einstein summation convention anyway, so presenting the additional of abstraction doesn't seem like there is any clear benefit to readers. <small><span style="display:inline-block;vertical-align:-.3em;line-height:.8em;text-align:right;text-shadow:black 1pt 1pt 1pt">[[User:Slawekb|<big>S</big>ławomir]]<br/><font color="red">[[User talk:Slawekb|Biały]]</font></span></small> 22:41, 19 November 2015 (UTC)


::The key point to understand is that the distinction between "covariant" and "contravariant" only makes sense for vector fields in the context of a preferred [[tangent bundle]] over an underlying manifold.
::It might be beneficial to change notation to such that vectors are bold-face lower-case letter, transformations are bold-face capital letters, while standard italics are used for scalars only. This convention is widespread in continuum mechanics, and, I believe, used in most elementary undergraduate courses. [[Special:Contributions/130.209.157.54|130.209.157.54]] ([[User talk:130.209.157.54|talk]]) 13:22, 14 January 2019 (UTC)
::Otherwise, all the structures could just be called simply "vectors" and the choice of one basis or another would be completely arbitrary.
::So, restricting ourselves to structures built from the tangent bundle, the vectors in the tangent bundle itself are called "contravariant", and the vectors in the dual or cotangent bundle are called "covariant". Tensor products of tangent and cotangent bundles may have both covariant and contravariant properties (depending on the index considered). [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 02:13, 3 January 2020 (UTC)


:::I'm afraid that in a strict sense, there are two distinct meanings in play here, and unless we distinguish them, confusion will ensue. One is a description of components, and mentioned above, and the meaning used by JRSpriggs essentially means "is an element of the (co)tangent bundle". The former makes sense in the context of a vector space and its dual space, independently of whether these are associated with a manifold. It is unfortunate that texts often conflate a tensor with its components with respect to a basis. I expect that the interpretation of a "contravariant vector" as being "an element of the tangent bundle" arises from exactly this conflation, and should be avoided (there is a better term: a "vector field") in favour of restricting its use to describing the behaviour of components with respect to changes of a basis. If in doubt about the confusion implicit in the mixed use of the terms, consider this conundrum: the set of components of a vector is contravariant (transform as the inverse of the transformation of the basis), whereas the basis (a tuple of vectors) is covariant (transform as the transformation of the basis by definition, in the first sense), yet we would describe the elements of the basis as being contravariant (in the sense of belonging to the tangent space), making them simultaneously "covariant" and "contravariant". Let's not build such confusion into the article, and restrict its meaning to (the no doubt original) sense. —[[User_talk:Quondum|Quondum]] 18:06, 31 March 2020 (UTC)
== Contravariant ==
I agree with others that the notation is distracting. As an offering for debate I submit the following for the explanation of contravariant.


I had precisely the same question, that I opened in math stackexchange. I haven't got any satisfactory answer yet. I hope somebody will pick this thread and continue the discussion. https://math.stackexchange.com/questions/4297246/conceptual-difference-between-covariant-and-contravariant-tensors <!-- Template:Unsigned IP --><small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[Special:Contributions/99.62.6.96|99.62.6.96]] ([[User talk:99.62.6.96#top|talk]]) 05:24, 29 December 2021 (UTC)</small> <!--Autosigned by SineBot-->
The Einstein summation convention is used; for emphasise only <math>k</math> is used as the dummy summation index.


== Covariance of gradient ==
An arbitrary point in <math>\mathcal{R}^n</math> has coordinates <math>\textbf{p}_O=(p^1,\cdots,p^n)</math>.
Introduce any basis vectors <math>X=\{\textbf{x}_1,\cdots,\textbf{x}_n\}</math>,
with <math>\textbf{x}_j =(x_j^1,\cdots,x_j^n)</math>,
which generate coordinate vectors <math>\textbf{p}_{X}=(v^1,\cdots,v^n)</math>,
such that <math>\textbf{p}_O= v^k\textbf{x}_k</math>
and hence <math>p^i=x^i_kv^k</math>. In matrix notation <math>\textbf{p}_O= \textbf{B}_{X} \textbf{p}_X</math> with <math>x^i_j</math> the <math>(i,j)</math> element of matrix <math>\textbf{B}_{X}</math> and <math>\textbf{p}_O</math>, <math>\textbf{p}_X</math> treated as column vectors.


I am a bit confused : this article takes the gradient to be a prime example of a "covariant vector", but the [[Gradient#Derivative|Gradient]] article claims that it is a contravariant vector. Which is correct? (Sorry if this is the wrong place to ask) --[[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82|talk]]) 19:56, 7 July 2020 (UTC)
Alternative basis vectors <math>E=\{\textbf{e}_1,\cdots,\textbf{e}_n\}</math> with <math>\textbf{e}_j =(e_j^1,\cdots,e_j^n)</math> generating <math>\textbf{p}_{E}=(r^1,\cdots,r^n)</math> such that <math>\textbf{p}_O= r^k\textbf{e}_k</math>, <math>p^i =e^i_kr^k</math>, <math>\textbf{p}_O= \textbf{B}_{E} \textbf{p}_E</math>.


:After thinking a little, I think I understand where my confusion comes from: the gradient of a function is covariant with respect to the input basis, but contravariant with respect to the output basis. Is this a valid interpretation? If it is, maybe this could be clarified in the lead of this article. --[[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82|talk]]) 20:08, 7 July 2020 (UTC)
Write <math>\textbf{e}_j= a^k_j\textbf{x}_k</math> then <math>e^i_j= x^i_ka^k_j</math> and <math>\textbf{B}_E = \textbf{B}_X\textbf{A}</math> with <math>e^i_j</math>, <math>a^i_j</math> the <math>(i,j)</math> element of matrices <math>\textbf{B}_E</math>, <math>\textbf{A}</math>.


::I do not understand your second comment. The gradient article is wrong because it is choosing the primary meaning as the one which includes the metric (i.e. the dot product) rather than the one which is merely the derivative. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 07:31, 9 July 2020 (UTC)
From <math>\textbf{B}_X \textbf{p}_X = \textbf{B}_E \textbf{p}_E = \textbf{B}_X\textbf{A} \textbf{p}_E</math> then <math>\textbf{p}_X\mapsto \textbf{p}_E</math> is given by <math>\textbf{p}_E = \textbf{A}^{-1}\textbf{p}_X</math> and hence <math>X\mapsto E</math> is a contravariant transformation.
::I back my position up with the reference [[Gravitation (book)]] page 59. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 05:12, 15 July 2020 (UTC)


This is simplistic, requires only elementary understanding of a vector, but still leaves elementary manipulations to the reader. It ties in with the idea of a matrix as a transformation and leads into the more difficult concepts of a dual space, covariant transformations and tensors. The notation is consistent with elementary tensor notation. <!-- Template:Unsigned --><small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[User:PatrickFoucault|PatrickFoucault]] ([[User talk:PatrickFoucault#top|talk]] • [[Special:Contributions/PatrickFoucault|contribs]]) 09:52, 14 September 2017 (UTC)</small> <!--Autosigned by SineBot-->
:::I meant that if a gradient <math>g</math> is seen as a linear form, say for instance from <math>\R^3</math> to <math>\R</math>, and <math>M \in GL_3(\R)</math> (resp. <math>N \in GL_1(\R)</math>) is an invertible matrix corresponding to a change of basis <math>B \rightarrow B'</math> in <math>\R^3</math> (resp. a change <math>C \rightarrow C'</math> in <math>\R</math>), then <math>g</math> will be expressed in the bases <math>B'</math> and <math>C'</math> as <math>N^{-1}gM</math> (assuming of course that <math>g</math> was originally expressed as a row matrix in the bases <math>B</math> and <math>C</math>). <!-- Template:Unsigned IP --><small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82#top|talk]]) 13:03, 10 July 2020 (UTC)</small> <!--Autosigned by SineBot-->
{{od}}
:I find it 1) not likely that the author of this bit is right and everyone else who writes on the topic is wrong, and 2) pretty obvious that gradient is covariant. If the temperature of a fluid drops by 1 degree per meter (a temperature gradient), then it's going to drop by ten degrees per ten meters, so if you change your unit of measure from one metre to 10 metres, the temperature gradient (change in degrees per unit of distance) likewise multiplies by 10. If the author of the "actually, gradient is contravariant" bit would care to plug that simple example into their <math display="block">\nabla f = \mathbf{e}_i (\nabla f)^i=\mathbf{e}_i \delta^{i}_j (\nabla f)^j=\mathbf{e}_i (T)_k^i(T^{-1})_j^k (\nabla f)^j\ ,</math> and explain why they get a different result, perhaps this would be helpful. [[Special:Contributions/203.13.3.93|203.13.3.93]] ([[User talk:203.13.3.93|talk]]) 03:38, 29 January 2024 (UTC)
::There are two different conventions for cpvariant versus contravariant; one gives primacy to covectors (diiferential forms) and on gives primacy to vectors. The gradient of a scalar field is a covector fiels; if vctors are covariant then it is contravariant and if vectors are contravariant then it is covatiant. I don't recall which convention the [[Gravitation (book)|"Texas Telephone Directory"]] (MTW) uses. -- [[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 15:15, 29 January 2024 (UTC)
:I think a few comments here have confusion based on the fact that the gradient of a function on R3 can be interpreted equally well either as a covariant or contravariant vector, because R3 has a canonical Riemannian metric. On a more general space, the derivative of a function is covariant (i.e. a 1-form) and if there is a metric it can be converted, in a way depending on the particular metric, to contravariant (i.e. a tangent vector). In common usage the former is called the differential of the function and the latter is called the gradient. [[User:Gumshoe2|Gumshoe2]] ([[User talk:Gumshoe2|talk]]) 15:55, 29 January 2024 (UTC)


== Example of vector which is not contravariant is arguably not a vector ==
== Organisation ==
Currently: "On the other hand, for instance, a triple consisting of the length, width, and height of a rectangular box could make up the three components of an abstract vector, but this vector would not be contravariant, since a change in coordinates on the space does not change the box's length, width, and height: instead these are scalars."
I advocate the article be organised along the following lines.
I think this is not helpful since there is no obvious meaning to the vector space of box [length, width, height]. What do vector scaling and vector addition correspond to? I suggest this example be removed. [[User:Intellec7|Intellec7]] ([[User talk:Intellec7|talk]]) 05:19, 28 August 2020 (UTC)


:OK. Go ahead and delete that sentence. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 14:47, 28 August 2020 (UTC)
* A very brief heuristic introduction about components transforming contra or co to the basis
* Brief history and etymology sections
* The above demonstration that a position vector always transforms contra. This also introduces the agreed notation.
* A similar demonstration regarding a vector that we would like to transform co
* Statement and link regarding the dual space and linear functionals
* Demonstration of a co transformation using a specific linear functional which should be the dot product.
* Discussion and links regarding tangents and normals and their use as bases.
* Mention of how this develops into tensors with links.
The demonstrations should be clear about the exact transformations. The current article is good, but it seems from the talk that further clarity is required. I think some of the introduction could be trimmed in favour of detailed worked examples of contra and co transformations. The current description of a covariant transformation could be clearer, and would benefit by being couched in terms of a specific functional such as the dot product, and possibly along the lines of the above contravariant demonstration. This would allow the concepts of row space and column space to emerge naturally and hence links to these articles. The inherent difference between contravariant and covariant is exposed without relying on heuristic explanations using tangents and normals.[[User:PatrickFoucault|Foucault]] ([[User talk:PatrickFoucault|talk]]) 03:52, 15 September 2017 (UTC)


== Geometrical construction of coordinates ==
:Your [https://en.wikipedia.org/enwiki/w/index.php?title=Covariance_and_contravariance_of_vectors&type=revision&diff=800885140&oldid=800789911 addition] was entirely [[wp:unsourced]] [[wp:original research]]. It does not comply with [[MOS:LEAD]] either. I have reverted it, for obviouis reasons. - [[User:DVdm|DVdm]] ([[User talk:DVdm|talk]]) 08:34, 16 September 2017 (UTC)
If you have a basis <math> \mathbf{e}^i </math> in a three dimensional Euclidean space you can construct the coordinates of a given point by drawing lines through the point parallel to each basis vector. Those lines will intersect with each other and the distance of the intersection point from the origin divided by the length of the corresponding basis vector gives you the covariant components <math> q_i </math>.
But how do you construct the coordinates in respect to the dual basis <math> \mathbf{e}_i </math> ???? [[Special:Contributions/2003:E7:2F3B:B0D8:11C:4108:841E:BA24|2003:E7:2F3B:B0D8:11C:4108:841E:BA24]] ([[User talk:2003:E7:2F3B:B0D8:11C:4108:841E:BA24|talk]]) 07:00, 17 April 2021 (UTC)


== Mis-use of the word "scalar" ==
:@[[User:PatrickFoucault|Foucault]]: I have not read your attempt in detail, but you cannot ignore the map that sends a contravariant vector to a covariant vector and vice versa. In [[Lorentz transformation#Covariant vectors]] you can find a similar overview (equally unsourced, but sourcable) in the special case that the map in question is the Lorentz metric. [[User:YohanN7|YohanN7]] ([[User talk:YohanN7|talk]]) 10:37, 16 September 2017 (UTC)
The word "scalar" is used in the page to mean something that multiplies a unit vector. But a scalar is supposed to be coordinate-free or gauge-invariant or invariant to changes of coordinates. The quantities that multiply unit vectors do not have this property, because the unit vectors change (and hence the components of the vectors change) as you change coordinates.
--[[User:Hogghogg|David W. Hogg]] ([[User talk:Hogghogg|talk]]) 12:58, 16 May 2021 (UTC)


:I tried to fix that. Let me know if there is still a problem. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 18:26, 16 May 2021 (UTC)
It is not my intention to ignore that map, nor my intention to write a definitive study. From the talk above, it seems some people feel the article could be improved. My attempt was at writing an introduction that would draw readers into reading further and also spark editors into making further constructive edits. If my attempt sparks activity, then good. The alternative is the article remains moribund.[[User:PatrickFoucault|Foucault]] ([[User talk:PatrickFoucault|talk]]) 02:48, 18 September 2017 (UTC)
:I don't share your rigid verdict of this article being ''moribund'', but of course, it is improvable. My two cents on possible improvement are that with all the usual considerations on "invariance to co- and contravariant transformations" between two frames/vectors, there is a third frame, camouflaged in the backdrop, most often. I think, e.g., all pictures of such frames (Euclidean or curvilinear) necessarily rely on this "observer's frame", and active and passive transformations might thus be judged from an other, possibly alien space. [[User:Purgy Purgatorio|Purgy]] ([[User talk:Purgy Purgatorio|talk]]) 06:13, 18 September 2017 (UTC)


:What about scalar densities (or if you refer to work from a concrete example, 'density' as in kg/m^3)? These are rank-zero tensors (or tensor fields) but nevertheless they are covariant. Can't recall the name, but one text I have read suggests that you can also have a 'scalar capacity', which can also be a field, which is a contravariant scalar. <!-- Template:Unsigned IP --><small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[Special:Contributions/203.13.3.89|203.13.3.89]] ([[User talk:203.13.3.89#top|talk]]) 03:26, 29 January 2024 (UTC)</small> <!--Autosigned by SineBot-->
OK. Not moribund. It has a B rating, is high priority and is in the top 500 articles viewed. So it seems the subject is worthwhile, a lot of good work has already gone into the article, but contributers to this talk page are still debating what the words contravariant and covariant mean. [[User:PatrickFoucault|Foucault]] ([[User talk:PatrickFoucault|talk]]) 10:04, 18 September 2017 (UTC)


== Vectors vs. Covectors ==
== Math under Three-dimensional Euclidean Space ==
Can someone look into this?


I have some "issues" with the fundamental jargon used in this article. I would like to help improve it; but I don't want to start an editing war. So, let me test the waters with a few comments:
While reading the following part,
Then the covariant coordinates of any vector '''v''' can be obtained by the [[dot product]] of '''v''' with the contravariant basis vectors: <math> q_1 = \mathbf{v} \cdot \mathbf{e}^1; \qquad q_2 = \mathbf{v} \cdot \mathbf{e}^2; \qquad q_3 = \mathbf{v} \cdot \mathbf{e}^3 .</math>
Likewise, the contravariant components of '''v''' can be obtained from the dot product of '''v''' with convariant basis vectors, viz.: <math> q^1 = \mathbf{v} \cdot \mathbf{e}_1; \qquad q^2 = \mathbf{v} \cdot \mathbf{e}_2; \qquad q^3 = \mathbf{v} \cdot \mathbf{e}_3 .</math>


Vectors and covectors are ''not'' the same thing. And they are both ''invariant'' under (proper, invertible) linear transformation. (Note: this is the passive/alias viewpoint of transformations). It is a semantic error to say that a vector is contravariant (or that a covector is covariant). The co/vectors, and tensors in general, are ''invariant'' under linear transformations. If the space has a metric, then one can "convert" a vector into a covector, and ''vice versa''. But the existence of a metric is not obligatory and, in fact, confuses people into thinking that vectors and covectors are fungible. They are not. Vectors are linear approximations to the curves defined by the intersection of <math>n-1</math> coordinate functions; covectors are linear functional approximations to the level (hyper)surfaces of a single coordinate function. The figure at the top of the article kind of hints at this, but then garbles the message by overlaying arrow quantities with level-surface quantities on the right-hand side. Too bad. Remove those blue arrows and you'd have a right proud representation of covectors in a cobasis.
I thought the math should have been this instead.
Then the covariant coordinates of any vector '''v''' can be obtained by the [[dot product]] of '''v''' with the contravariant basis vectors: <math> q_1 = \mathbf{v} \cdot \mathbf{e}_1; \qquad q_2 = \mathbf{v} \cdot \mathbf{e}_2; \qquad q_3 = \mathbf{v} \cdot \mathbf{e}_3 .</math>
Likewise, the contravariant components of '''v''' can be obtained from the dot product of '''v''' with convariant basis vectors, viz.: <math> q^1 = \mathbf{v} \cdot \mathbf{e}^1; \qquad q^2 = \mathbf{v} \cdot \mathbf{e}^2; \qquad q^3 = \mathbf{v} \cdot \mathbf{e}^3 .</math>


Co/contra-variance is a property of the components and of the basis elements. For a vector <math>(\mathbf{v})</math>, the components <math>(v^i)</math> are contravariant and the basis vectors <math>(\mathbf{e}_i)</math> are covariant; for a covector <math>(\boldsymbol\omega)</math>, the components <math>(\omega_i)</math> are covariant and the basis covectors <math>(\mathbf{e}^i)</math> are contravariant. In either case, when you contract the components with the basis—one of which is covariant and the other contravariant—then you get an invariant quantity, as required of a tensor.
But then, the following makes even less sense. It would couple the covariant (contravariant) coordinates to one another through the covariant (contravariant) bases.
and we can convert from contravariant to covariant basis with <math>q^i = \mathbf{v}\cdot \mathbf{e}_i = (q^j \mathbf{e}_j)\cdot \mathbf{e}_i = (\mathbf{e}_j\cdot\mathbf{e}_i) q^j </math>
and <math>q_i = \mathbf{v}\cdot \mathbf{e}^i = (q_j \mathbf{e}^j)\cdot \mathbf{e}^i = (\mathbf{e}^j\cdot\mathbf{e}^i) q_j .</math>
[[User:D4nn0v|D4nn0v]] ([[User talk:D4nn0v|talk]]) 08:38, 29 November 2017 (UTC)


I won't try to define/defend here (yet;-) what co/contra-variant mean. (Spoiler alert: ''contra''variant quantities transform as the Jacobian of a coordinate transformation; ''co''variant quantities transform as the ''inverse'' Jacobian; this seems backwards to what I, for one, would expect from the concepts of ''co-'' and ''contra-''; but it is what it is!)
<br>
::I tried to fix the problem. Let me know, if you see anything I missed or disagree with what I did. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 02:18, 30 November 2017 (UTC)


To whomever has purview over this article: if these comments make sense and seem worth the trouble of editing the article, please let me know and I'll try to collaborate. On the other hand, if you think these are distinctions without a difference—or worse, misguided—then I'll stand down.--[[User:ScriboErgoSum|ScriboErgoSum]] ([[User talk:ScriboErgoSum|talk]]) 08:25, 15 November 2021 (UTC)
<br>
::::Looks good! [[User:D4nn0v|D4nn0v]] ([[User talk:D4nn0v|talk]]) 02:16, 4 December 2017 (UTC)


== NPOV ==
== Confusion between vector components, vector coordinate and the reference axes. ==
In the second paragraph under Introduction of there are too many undefined terms which are very confusing. While the component of the vector are the <v<sub>1</sub>,v<sub>2</sub>,v<sub>3</sub>> and the reference axis is given to mean the coordinate basis vector, its not clear what does the word "coordinate" refers to. From the example involving the change of scale of the reference axis, it's quite easy to understand what how the components of the vector vary inversely to change of scale of the basis vectors. But the second paragraph under Introduction states that components of contravariant vectors vary inversely to the basis vector(which is clearly understood) but "transform as the coordinates do". What do coordinates mean here? the coordinate of the vector which or the coordinate axis?. The word coordinate has been used multiple times without an explanation as to what it means while it is not at all required as the concept is clear by stating how the components change with the change of basis(ie the reference axes).


The article describes covariance and contravariance in terms of coordinates and components, a perspective that is rather dated. The terms have a meaning independent of any choice of basis or coordinates, and the article should reflect that. There is a lot of variation in the literature, but essentially there are three styles:
granzer92 [[User:Granzer92|Granzer92]] ([[User talk:Granzer92|talk]]) 14:09, 10 June 2018 (UTC)


#Define the tangent and cotangent bundles independently, then prove duality.
:I removed some misinformation from the lead and the introduction. I hope that helps.
##Authors often define tangent vectors as equivalence classes of curves through a point.
:The [[coordinate system]] on a manifold generally determines the choice of basis vectors for the tangent space at each point on the manifold. That is why it is relevant. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 02:33, 11 June 2018 (UTC)
##Authors often define cotangent vectors in the language of [[Germ (mathematics)|germs]].
#Define the tangent bundle, define the cotangent space at a point as the dual of the tangent space at that point and then define the cotangent bundle.
#Define the cotangent bundle, define the tangent space at a point as the dual of the cotangent space at that point and then define the tangent bundle.


Tensors can then be defined as either tensor products or as multilinear maps. It is common to just classify tensors by the covariant and contravariant ranks, but if there is a (pseudo)metric involved then order matters because of raising and lowering of indexes. --[[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 11:32, 1 March 2022 (UTC)
== Standard definition apparent inconsistency ==
:This article mostly describes tensors; what you are describing is [[tensor field]]. But taking your point, there should be some section for the tensor product language on this page. Even so, there is no need to choose one way over another. (I object to the idea that bases and coordinates are dated.) [[User:Gumshoe2|Gumshoe2]] ([[User talk:Gumshoe2|talk]]) 07:26, 13 March 2022 (UTC)
<s>Could someone please explain the fallacy in the following?</s>
::
::There is a large amount of material in the [[Tensors]] article that does not belong there, but should rather be in [[Tensor fields]]. The distinction between ''covariant'' and ''contravariant'' is really only relevant for tensor fields on a manifold, but as long as it is in this article the text should reflect its character.
::I didn't say that coordinates and bases are dated, but rather that defining, e.g., tensor, covariant, in terms of coordinates and bases rather than intrinsically is dated. --[[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 12:51, 13 March 2022 (UTC)
:::I agree that the tensor product definition should be given here, but I think it should be given together with the present one. Why do you say that co(/ntra)variance is only relevant for tensor fields? There is of course a distinction between an element of a vector space and an element of the dual vector space, for instance. [[User:Gumshoe2|Gumshoe2]] ([[User talk:Gumshoe2|talk]]) 17:37, 13 March 2022 (UTC)
::::Whoops! Yes, of course there is a difference between {{var|V}} and {{var|V*}} for an abstract vector space {{var|V}}, not just for tangent spaces. --[[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 19:21, 13 March 2022 (UTC)


==Inconsistency of note 1 with the main text==
Suppose that in <math>\mathbf{R}^{3}</math> we change from a basis <math>B</math> in units of meters to a basis <math>\overline{B}</math> in units of centimeters. That is,
I am adding this (3/26/2022) without reading the below because I have a comment on the definition section. We have {{nowrap|1='''f''' = (''X''<sub>1</sub>, ..., ''X''<sub>''n''</sub>)}} with each of the Xis being basis a vector. I was going to add a remark that said this makes '''f''' a matrix and indeed it is used as a matrix in the unnumbered equation '''v'''='''f''' '''v'''['''f''']. I decided not
to add that comment as it contradicts Note 1. In the note preceding Eq 1 it says "regarding '''f''' as a row vector whose entries are the elements of the basis". Maybe I am naive but I find this pretty confusing as I've always considered matrices and vectors to be different objects. If '''f''' is to be considered a row vector but with each element a basis vector instead of just a number (as one usually thinks of vectors) this needs to be explained. If the note is incorrect then it should be removed. <!-- Template:Unsigned --><span class="autosigned" style="font-size:85%;">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[User: 76.113.29.12| 76.113.29.12]] ([[User talk: 76.113.29.12#top|talk]] • [[Special:Contributions/ 76.113.29.12|contribs]]) 14:45, 26 March 2022 (UTC)</span>


:I removed the template. It is sometimes useful when dealing with matrices to consider a matrix as a column vector of row vectors or a row vector of column vectors. In this sense, a vector is just a list of some object even though it's entries are not strictly from a field. I tend to agree with your level of scrutiny, which if applied would require we don't use the word vector (see [https://math.stackexchange.com/questions/1854424/are-the-elements-of-a-module-also-called-vectors here]). The wording of vector could be changed to that of list, but I don't think that would be a helpful change and actually could be a little detrimental, so I am leaving it. [[Special:Contributions/69.166.46.156|69.166.46.156]] ([[User talk:69.166.46.156|talk]]) 19:35, 25 April 2022 (UTC)
:<math> \mathbf{\overline{b}}^{i} = \left(\frac{1}{100}\right)\mathbf{b}^{i}, \quad (1 \le i \le 3). </math>


== Relative vectors? ==
Then the coordinate transformation is
{{NumBlk|:|<math> \overline{x}^{i} = (100)x^{i}, \quad (1 \le i \le 3), </math>|{{EquationRef|1}}}}


Should the article discuss relative vectors, whose transformation includes a power of the transformation determinant as a factor? In more modern language, these are tensor products of vectors with [[tensor density|tensor densities]], or for [[orientable manifold]]s, [[Lift (mathematics)|liftings]] of [[line bundle]]s. -- [[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 14:31, 13 November 2023 (UTC)
and the coordinate transformation in matrix form is
{{NumBlk|:|<math> \mathbf{A} = \begin{pmatrix}
100 & 0 & 0 \\
0 & 100 & 0 \\
0 & 0 & 100
\end{pmatrix}. </math>|{{EquationRef|2}}}}


: This seems like a good place for it. Note that in [[tensor]] there is some content on tensor densities which uses notation compatible with this article. [[User:Tito Omburo|Tito Omburo]] ([[User talk:Tito Omburo|talk]]) 22:31, 15 March 2024 (UTC)
A position vector


== Orthogonal is not enough ==
{{NumBlk|:|<math> \mathbf{r} = 3\mathbf{b}^{1} + 4\mathbf{b}^{2} + 12\mathbf{b}^{3} </math>|{{EquationRef|3}}}}


{{ping|JRSpriggs}} In [[special:permalink/1233199815|permalink/1233199815]] I changed {{tqq|in [[three-dimensional|3-d]] general ''[[curvilinear coordinates]]'' {{nowrap|(''q''{{sup|1}}, ''q''{{sup|2}}, ''q''{{sup|3}})}}, a [[tuple]] of numbers to define a point in a [[position space]]. Note the basis and cobasis coincide only when the basis is [[orthogonal basis|orthogonal]]}} to {{tqq|in [[three-dimensional|3-d]] general ''[[curvilinear coordinates]]'' {{nowrap|(''q''{{sup|1}}, ''q''{{sup|2}}, ''q''{{sup|3}})}}, a [[tuple]] of numbers to define a point in a [[position space]]. Note the basis and cobasis coincide only when the basis is [[orthogonal basis|orthonormall]]}}. In [[special:permalink/1233348907|permalink/1233348907]], [[user:JRSpriggs|JRSpriggs]] reverted to the to last version by Derek farn, undoing edits by 76.116.252.35, me and [[user:Antoni Parellada |Antoni Parellada ]].
with magnitude <math>|\mathbf{r}| = 13\text{ m}</math> is transformed to
[[Orthogonality (mathematics)|Orthogonality]] ia not a strong enough condition for the basis and cobasis to coincide; they have to be both orthogonal and of norm 1, i.e., [[orthonormal]]. -- [[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 14:33, 12 July 2024 (UTC)


:I agree it should be orthonormal. It seems the erroneous statement has been there unchallenged since 09:11, 3 September 2012, with a reference to a reliable source (but no page number). I don't have a copy of that book, so I can't tell if it's been misinterpreted and I don't have to hand a reliable source of my own. @[[User:Chatul|Chatul]], do you have a reliable source for this? By the way, the orthonormality is already mentioned in the article, in the last sentence of the "[[Covariance and contravariance of vectors#Three-dimensional Euclidean space|Three-dimensional Euclidean space]]" subsection. <span style="box-shadow:2px 2px 6px #999">[[User:Dr Greg|<b style="color:#FFF8C0;background:#494">&nbsp;Dr&nbsp;Greg&nbsp;</b>]][[User talk:Dr Greg|<span style="color:#494;background:#FFF8C0">&nbsp;<small>talk</small>&nbsp;</span>]]</span> 17:52, 12 July 2024 (UTC)
{{NumBlk|:|<math> \mathbf\overline{r} = 300\mathbf{\overline{b}}^{1} + 400\mathbf{\overline{b}}^{2} + 1200\mathbf{\overline{b}}^{3} </math>|{{EquationRef|4}}}}
::I corrected it and added {{tl|specify}}. MTW is an unimpeachable source, but a quick search in my dead tree version turned up nothing relevant; I'll check the index for [[dual basis]] and [[Tetrad (general relativity)|Tetrad]].

::I was tempted to add a {{tl|cn}} to {{alink|Three-dimensional Euclidean space}} but thought [[WP:BLUESKY|BLUESKY]] might apply. -- [[User:Chatul|Shmuel (Seymour J.) Metz Username:Chatul]] ([[User talk:Chatul|talk]]) 06:53, 14 July 2024 (UTC)
with magnitude <math>|\mathbf\overline{r}| = 1300\text{ cm}.</math>

Suppose that a scalar function <math>f(x^{i}) = -2{x}^{1}</math> is defined in a region containing '''r'''. Then,

{{NumBlk|:|<math> \frac{\partial{f}}{\partial{{x}^{1}}} = -2, \frac{\partial{f}}{\partial{{x}^{2}}} = \frac{\partial{f}}{\partial{{x}^{3}}} = 0, </math>|{{EquationRef|5}}}}

the gradient vector is

{{NumBlk|:|<math> \mathbf{\nabla{f}} = \frac{\partial{f}}{\partial{{x}^{1}}}\mathbf{b}^{1} + \frac{\partial{f}}{\partial{{x}^{2}}}\mathbf{b}^{2} + \frac{\partial{f}}{\partial{{x}^{3}}}\mathbf{b}^{3} = -2\mathbf{b}^{1}, </math>|{{EquationRef|6}}}}

and the gradient vector at '''r''',

{{NumBlk|:|<math> \mathbf{\nabla{f}}(\mathbf{r}) = -2\mathbf{b}^{1}, </math>|{{EquationRef|7}}}}

with magnitude <math>|\mathbf{\nabla{f}}(\mathbf{r})| = -2\text{ m}^{-1}</math>, is transformed to

{{NumBlk|:|<math> \mathbf{\overline{\nabla{f}}}(\mathbf{\overline{r}}) = -0.02\mathbf{\overline{b}}^{1}, </math>|{{EquationRef|8}}}}

with magnitude <math>|\mathbf{\overline{\nabla{f}}}(\mathbf{\overline{r}})| = -0.02\text{ cm}^{-1}.</math>

While the position vector '''r''' and the gradient vector <math>\mathbf{\nabla{f}}(\mathbf{r})</math> are ''invariant'', the components of the position vector in equations ({{EquationNote|3}}) and ({{EquationNote|4}}) transform ''inversely'' as the basis vectors, and the components of the gradient vector in equations ({{EquationNote|7}}) and ({{EquationNote|8}}) transform ''directly'' as the basis vectors.

Now, most textbooks agree<ref>{{ citation | last1 = Kay | first1 = David C. | title = Schaum's Outline of Theory and Problems of Tensor Calculus | location = New York | publisher = [[McGraw-Hill]] | year = 1988 | isbn = 0-07-033484-6 | pages = 26-27 }}</ref> that a vector '''u''' is a ''contravariant vector'' if its components <math>(T^{i})</math> and <math>(\overline{T}^{i})</math> relative to the respective coordinate systems <math>(x^{i})</math> and <math>(\overline{x}^{i})</math> transform according to

{{NumBlk|:|<math> \overline{T}^{i} = T^{r}\frac{\partial{\overline{x}^{i}}}{\partial{x^{r}}}, \quad (1 \le i \le 3) </math>|{{EquationRef|9}}}}

and that a vector '''w''' is a ''covariant vector'' if its components <math>(T_{i})</math> and <math>(\overline{T}_{i})</math> relative to the respective coordinate systems <math>(x^{i})</math> and <math>(\overline{x}^{i})</math> transform according to

{{NumBlk|:|<math> \overline{T}_{i} = T_{r}\frac{\partial{x^{r}}}{\partial{\overline{x}^{i}}}, \quad (1 \le i \le 3), </math>|{{EquationRef|10}}}}

<s>but equations ({{EquationNote|4}}) and ({{EquationNote|8}}) seem to indicate the exact ''opposite'' of equations ({{EquationNote|9}}) and ({{EquationNote|10}}). Why?</s>—[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 17:44, 24 November 2018 (UTC)

:There is an error in your comment right at the beginning. So I stopped reading it at that point. If <math>x^{i}</math> is the position in meters and <math>\overline{x}^{i}</math> is the position in centimeters, then the conversion is just:
::<math> \overline{x}^{i} = 100 \cdot x^{i}, \quad (1 \le i \le 3). </math>
:OK? [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 22:46, 24 November 2018 (UTC)

::<s>The <math>x^{i}</math>, with <math>|x^{i}| = 1 \text{ m}</math>, are the old basis vectors; the <math>\overline{x}^{i}</math>, with <math>|\overline{x}^{i}| = 0.01 \text{ m} = 1 \text{ cm}</math> are the new basis vectors.</s>—[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 03:17, 25 November 2018 (UTC)

:::Maybe this helps:
:::Let's have two ordered bases of a 3-D vector space over <math>\mathbb R,</math> consisting of three orthogonal vectors each
::::<math>\{e_i\mid i\in \{1,2,3\}\}\quad</math> and <math>\quad\{\bar e_i\mid i\in \{1,2,3\}\}\quad</math> with
::::<math>||e_i|| = 1\text{m}\quad</math> and <math>\quad||\bar e_i|| = 1\text{cm}\quad</math> for <math>i\in \{1,2,3\}.</math> (To be honest, I am unsure how to formally conflate a multiplicative group of units with the norm of the vector space)
:::Further, let (for simplicity, and satisfying the above)
::::<math>\bar e_i = \frac{1}{100} e_i,\quad</math> again for <math>i\in \{1,2,3\}.</math>
:::This yields the matrix <math>A</math> from above. Now let's have a vector, and its decompositions wrt the two bases (adopting Gaussian summation convention)
:::: <math>r = r^i e_i = \bar r^i \bar e_i.</math>
:::For the last equalities to hold, the scalar coefficients must satisfy
::::<math> \bar r^i = 100 r^i\quad</math> for <math>i\in \{1,2,3\}.</math>
:::This yields the relation for coefficients, given by JRSpriggs above. Maybe it's all about the vectors, formed from the coefficients suitably arranged in tuples (and freely identified with abstract vectors) that vary ''contravariantly''? (I'm struggling myself.)

:::OK? [[User:Purgy Purgatorio|Purgy]] ([[User talk:Purgy Purgatorio|talk]]) 13:14, 25 November 2018 (UTC)

::::This makes perfect sense to me, and I believe this is what I wrote in equations ({{EquationNote|1}},{{EquationNote|2}},{{EquationNote|3}},{{EquationNote|4}}), but I do not see how equations ({{EquationNote|9}},{{EquationNote|10}}) agree with this. For example, equation ({{EquationNote|1}}) seems to imply that for the basis vectors, <math>x^{i}</math> and <math>\overline{x}^{i}</math>,

{{NumBlk|:::::|<math> \frac{\partial{\overline{x}^{i}}}{\partial{x^{i}}} = \frac{1}{100}, \quad (1 \le i \le 3)</math>|{{EquationRef|11}}}}

:::: (the other partial derivatives are zero), but then equation ({{EquationNote|9}}) for the components <math>(T^{i})</math> and <math>(\overline{T}^{i})</math> of <math>(\mathbf{r})</math> and <math>(\mathbf\overline{r})</math> would be

{{NumBlk|:::::|<math> \overline{T}^{i} = T^{i}\frac{1}{100}, \quad (1 \le i \le 3), </math>|{{EquationRef|12}}}}

::::in contradiction to equation ({{EquationNote|4}}).

::::I have faith that equations ({{EquationNote|9}},{{EquationNote|10}}) in textbooks are somehow correct, but because they look incorrect to me, I evidently have a misconception somewhere. I am trying to determine where and what that misconception is—[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 20:27, 25 November 2018 (UTC)

:::::I do not know what you mean by equation (2) because you do not explain how you are using '''A'''. Equation (3) is obvious bull-shit. It should be
::::::<math> x^1 = 3; x^2 = 4; x^3 = 12 .</math>
:::::Again I stopped reading at that point until you clean up your act. You ''must'' explain what all the variables in your equations mean or you will never get your head straight. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 01:58, 26 November 2018 (UTC)

::::::I regret having mistaken the question. I thought to perceive a mix up of scalar coefficients and vectors, wherefore I dismissed the <math>x^i</math>s, seemingly used for both kinds, and introduced the <math>e_i</math>s for vectors and the <math>r^i</math>s for scalars, and wrote that boring triviality. Maybe, I tripped over the possibility of having ''abstract indices'' to denote vectors, but again, I have no formal conception for these. [[User:Purgy Purgatorio|Purgy]] ([[User talk:Purgy Purgatorio|talk]]) 07:08, 26 November 2018 (UTC)

:::::::I think I see where some of my misconceptions were. Correct me if I am wrong. (By chance, I discovered something in one of my books that clued me in, although it was not obvious.) Most textbooks that I have seen for linear algebra and tensors do not make clear the distinction between basis vectors, coordinate vectors, coordinates, and components. I tend to agree with [[User:Granzer92|Granzer92]] ([[User talk:Granzer92|talk]]) in the previous section, that the [[Covariance and contravariance of vectors#Introduction|Introduction]] did not make this clear either, and still does not. I have edited my original post above. Now equations ({{EquationNote|4}}) and ({{EquationNote|8}}) seem to agree with equations ({{EquationNote|9}}) and ({{EquationNote|10}}). Please let me know if I have this correct now.–[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 22:56, 27 November 2018 (UTC)

::::::::I agree to the reservations addressed by Granzer92, and admit not being a jour with JRSpriggs improvements. To my impression, much of this potential of confusion is caused by the wide spread, convenient notation of a '''basis'''-transformation, involving -say- "v-vectors" with bases-vectors as coordinates, and matrices of scalars as linear maps, without (sufficiently) emphasizing that the "v-vectors" live in "another" space than the basis-vectors, and that these spaces just share their scalars. The didactic migration from coordinate-bound to coordinate-free has not fully matured, yet, imho. [[User:Purgy Purgatorio|Purgy]] ([[User talk:Purgy Purgatorio|talk]]) 08:49, 28 November 2018 (UTC)

{{Reflist-talk}}

== Co-/contra- variance of 'vectors' (per se) or of their components ==
It is my understanding that a vector, per se (i.e. not its representation), is neither covariant or contravariant. Instead covariance or contravariance refers to a given representation of the vector, depending on the basis being used. For example, one can write the same vector in either manner as, <math>\vec{A} = a^i e_i = a_i e^i</math>. I think this point (in addition to the variance topic as a whole) can be both subtle and confusing to people first learning these topics, and thus the terminology should be used very carefully, consistently, and rigorously. I tried to change some of the terminology in the article to say, "vectors with covariant components" instead of "covariant vectors" (for example), but this has been reversed as inaccurate. So I wanted to open a discussion in case I am mistaken or others disagree. @JRSpriggs. [[User:Zhermes|Zhermes]] ([[User talk:Zhermes|talk]]) 16:45, 2 January 2020 (UTC)

:I have several textbooks that describe ''covariance'' and ''contravariance'' of tensors. Most of them refer to the tensors themselves as having these properties; however, some of them indicate that these properties apply only to the components and that the tensors are ''invariant''. I am inclined to agree with the latter, that is, that only the components change—not the tensors. I think we should point out in the article two things: 1. what we think is the correct parlance, and 2. the fact that some textbooks say otherwise. I can supply citations.—[[User:Anita5192|Anita5192]] ([[User talk:Anita5192|talk]]) 17:54, 2 January 2020 (UTC)

::The key point to understand is that the distinction between "covariant" and "contravariant" only makes sense for vector fields in the context of a preferred [[tangent bundle]] over an underlying manifold.
::Otherwise, all the structures could just be called simply "vectors" and the choice of one basis or another would be completely arbitrary.
::So, restricting ourselves to structures built from the tangent bundle, the vectors in the tangent bundle itself are called "contravariant", and the vectors in the dual or cotangent bundle are called "covariant". Tensor products of tangent and cotangent bundles may have both covariant and contravariant properties (depending on the index considered). [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 02:13, 3 January 2020 (UTC)

:::I'm afraid that in a strict sense, there are two distinct meanings in play here, and unless we distinguish them, confusion will ensue. One is a description of components, and mentioned above, and the meaning used by JRSpriggs essentially means "is an element of the (co)tangent bundle". The former makes sense in the context of a vector space and its dual space, independently of whether these are associated with a manifold. It is unfortunate that texts often conflate a tensor with its components with respect to a basis. I expect that the interpretation of a "contravariant vector" as being "an element of the tangent bundle" arises from exactly this conflation, and should be avoided (there is a better term: a "vector field") in favour of restricting its use to describing the behaviour of components with respect to changes of a basis. If in doubt about the confusion implicit in the mixed use of the terms, consider this conundrum: the set of components of a vector is contravariant (transform as the inverse of the transformation of the basis), whereas the basis (a tuple of vectors) is covariant (transform as the transformation of the basis by definition, in the first sense), yet we would describe the elements of the basis as being contravariant (in the sense of belonging to the tangent space), making them simultaneously "covariant" and "contravariant". Let's not build such confusion into the article, and restrict its meaning to (the no doubt original) sense. —[[User_talk:Quondum|Quondum]] 18:06, 31 March 2020 (UTC)

== Introduction for the layman ==

I would add a paragraph to the introduction, which is easier to understand. Maybe something like this:

'''contravariant vectors'''

Let's say we have three base vectors a, b and c. Each one has the length 1 meter. d = (3,2,4) is a vector (≙ (3m,2m,4m)).If we now double the length of every base vector, so that |a| = |b| = |c| = 2m, then d must be (1.5, 1, 2) using the new a, b, c basis.(but d would still be (3m,2m,4m))

'''covariant vectors'''

Let's say f is a scalar function and the base of the coordinate system is a, b and c. And suppose |a| = |b| = |c| = 1 meter. Then suppose that ∇f=(2,5,9); so that the slope in x-direction is 2/ meter (2 per meter). If we now double the length of each base vector, so that |a| = |b| = |c| = 2m, ∇f becomes (4,10,18). The slope in x-direction is the same: 4/2m = 2/m.

[[User:CaffeineWitcher|CaffeineWitcher]] ([[User talk:CaffeineWitcher|talk]]) 12:59, 23 May 2020 (UTC)

== Covariance of gradient ==

I am a bit confused : this article takes the gradient to be a prime example of a "covariant vector", but the [[Gradient#Derivative|Gradient]] article claims that it is a contravariant vector. Which is correct? (Sorry if this is the wrong place to ask) --[[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82|talk]]) 19:56, 7 July 2020 (UTC)

:After thinking a little, I think I understand where my confusion comes from: the gradient of a function is covariant with respect to the input basis, but contravariant with respect to the output basis. Is this a valid interpretation? If it is, maybe this could be clarified in the lead of this article. --[[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82|talk]]) 20:08, 7 July 2020 (UTC)

::I do not understand your second comment. The gradient article is wrong because it is choosing the primary meaning as the one which includes the metric (i.e. the dot product) rather than the one which is merely the derivative. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 07:31, 9 July 2020 (UTC)
::I back my position up with the reference [[Gravitation (book)]] page 59. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 05:12, 15 July 2020 (UTC)

:::I meant that if a gradient <math>g</math> is seen as a linear form, say for instance from <math>\R^3</math> to <math>\R</math>, and <math>M \in GL_3(\R)</math> (resp. <math>N \in GL_1(\R)</math>) is an invertible matrix corresponding to a change of basis <math>B \rightarrow B'</math> in <math>\R^3</math> (resp. a change <math>C \rightarrow C'</math> in <math>\R</math>), then <math>g</math> will be expressed in the bases <math>B'</math> and <math>C'</math> as <math>N^{-1}gM</math> (assuming of course that <math>g</math> was originally expressed as a row matrix in the bases <math>B</math> and <math>C</math>). <!-- Template:Unsigned IP --><small class="autosigned">—&nbsp;Preceding [[Wikipedia:Signatures|unsigned]] comment added by [[Special:Contributions/93.25.93.82|93.25.93.82]] ([[User talk:93.25.93.82#top|talk]]) 13:03, 10 July 2020 (UTC)</small> <!--Autosigned by SineBot-->

== Example of vector which is not contravariant is arguably not a vector ==
Currently: "On the other hand, for instance, a triple consisting of the length, width, and height of a rectangular box could make up the three components of an abstract vector, but this vector would not be contravariant, since a change in coordinates on the space does not change the box's length, width, and height: instead these are scalars."
I think this is not helpful since there is no obvious meaning to the vector space of box [length, width, height]. What do vector scaling and vector addition correspond to? I suggest this example be removed. [[User:Intellec7|Intellec7]] ([[User talk:Intellec7|talk]]) 05:19, 28 August 2020 (UTC)

:OK. Go ahead and delete that sentence. [[User:JRSpriggs|JRSpriggs]] ([[User talk:JRSpriggs|talk]]) 14:47, 28 August 2020 (UTC)

Latest revision as of 06:53, 14 July 2024

Co-/contra- variance of 'vectors' (per se) or of their components

[edit]

It is my understanding that a vector, per se (i.e. not its representation), is neither covariant or contravariant. Instead covariance or contravariance refers to a given representation of the vector, depending on the basis being used. For example, one can write the same vector in either manner as, . I think this point (in addition to the variance topic as a whole) can be both subtle and confusing to people first learning these topics, and thus the terminology should be used very carefully, consistently, and rigorously. I tried to change some of the terminology in the article to say, "vectors with covariant components" instead of "covariant vectors" (for example), but this has been reversed as inaccurate. So I wanted to open a discussion in case I am mistaken or others disagree. @JRSpriggs. Zhermes (talk) 16:45, 2 January 2020 (UTC)[reply]

I have several textbooks that describe covariance and contravariance of tensors. Most of them refer to the tensors themselves as having these properties; however, some of them indicate that these properties apply only to the components and that the tensors are invariant. I am inclined to agree with the latter, that is, that only the components change—not the tensors. I think we should point out in the article two things: 1. what we think is the correct parlance, and 2. the fact that some textbooks say otherwise. I can supply citations.—Anita5192 (talk) 17:54, 2 January 2020 (UTC)[reply]
The key point to understand is that the distinction between "covariant" and "contravariant" only makes sense for vector fields in the context of a preferred tangent bundle over an underlying manifold.
Otherwise, all the structures could just be called simply "vectors" and the choice of one basis or another would be completely arbitrary.
So, restricting ourselves to structures built from the tangent bundle, the vectors in the tangent bundle itself are called "contravariant", and the vectors in the dual or cotangent bundle are called "covariant". Tensor products of tangent and cotangent bundles may have both covariant and contravariant properties (depending on the index considered). JRSpriggs (talk) 02:13, 3 January 2020 (UTC)[reply]
I'm afraid that in a strict sense, there are two distinct meanings in play here, and unless we distinguish them, confusion will ensue. One is a description of components, and mentioned above, and the meaning used by JRSpriggs essentially means "is an element of the (co)tangent bundle". The former makes sense in the context of a vector space and its dual space, independently of whether these are associated with a manifold. It is unfortunate that texts often conflate a tensor with its components with respect to a basis. I expect that the interpretation of a "contravariant vector" as being "an element of the tangent bundle" arises from exactly this conflation, and should be avoided (there is a better term: a "vector field") in favour of restricting its use to describing the behaviour of components with respect to changes of a basis. If in doubt about the confusion implicit in the mixed use of the terms, consider this conundrum: the set of components of a vector is contravariant (transform as the inverse of the transformation of the basis), whereas the basis (a tuple of vectors) is covariant (transform as the transformation of the basis by definition, in the first sense), yet we would describe the elements of the basis as being contravariant (in the sense of belonging to the tangent space), making them simultaneously "covariant" and "contravariant". Let's not build such confusion into the article, and restrict its meaning to (the no doubt original) sense. —Quondum 18:06, 31 March 2020 (UTC)[reply]

I had precisely the same question, that I opened in math stackexchange. I haven't got any satisfactory answer yet. I hope somebody will pick this thread and continue the discussion. https://math.stackexchange.com/questions/4297246/conceptual-difference-between-covariant-and-contravariant-tensors — Preceding unsigned comment added by 99.62.6.96 (talk) 05:24, 29 December 2021 (UTC)[reply]

Covariance of gradient

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I am a bit confused : this article takes the gradient to be a prime example of a "covariant vector", but the Gradient article claims that it is a contravariant vector. Which is correct? (Sorry if this is the wrong place to ask) --93.25.93.82 (talk) 19:56, 7 July 2020 (UTC)[reply]

After thinking a little, I think I understand where my confusion comes from: the gradient of a function is covariant with respect to the input basis, but contravariant with respect to the output basis. Is this a valid interpretation? If it is, maybe this could be clarified in the lead of this article. --93.25.93.82 (talk) 20:08, 7 July 2020 (UTC)[reply]
I do not understand your second comment. The gradient article is wrong because it is choosing the primary meaning as the one which includes the metric (i.e. the dot product) rather than the one which is merely the derivative. JRSpriggs (talk) 07:31, 9 July 2020 (UTC)[reply]
I back my position up with the reference Gravitation (book) page 59. JRSpriggs (talk) 05:12, 15 July 2020 (UTC)[reply]
I meant that if a gradient is seen as a linear form, say for instance from to , and (resp. ) is an invertible matrix corresponding to a change of basis in (resp. a change in ), then will be expressed in the bases and as (assuming of course that was originally expressed as a row matrix in the bases and ). — Preceding unsigned comment added by 93.25.93.82 (talk) 13:03, 10 July 2020 (UTC)[reply]
I find it 1) not likely that the author of this bit is right and everyone else who writes on the topic is wrong, and 2) pretty obvious that gradient is covariant. If the temperature of a fluid drops by 1 degree per meter (a temperature gradient), then it's going to drop by ten degrees per ten meters, so if you change your unit of measure from one metre to 10 metres, the temperature gradient (change in degrees per unit of distance) likewise multiplies by 10. If the author of the "actually, gradient is contravariant" bit would care to plug that simple example into their and explain why they get a different result, perhaps this would be helpful. 203.13.3.93 (talk) 03:38, 29 January 2024 (UTC)[reply]
There are two different conventions for cpvariant versus contravariant; one gives primacy to covectors (diiferential forms) and on gives primacy to vectors. The gradient of a scalar field is a covector fiels; if vctors are covariant then it is contravariant and if vectors are contravariant then it is covatiant. I don't recall which convention the "Texas Telephone Directory" (MTW) uses. -- Shmuel (Seymour J.) Metz Username:Chatul (talk) 15:15, 29 January 2024 (UTC)[reply]
I think a few comments here have confusion based on the fact that the gradient of a function on R3 can be interpreted equally well either as a covariant or contravariant vector, because R3 has a canonical Riemannian metric. On a more general space, the derivative of a function is covariant (i.e. a 1-form) and if there is a metric it can be converted, in a way depending on the particular metric, to contravariant (i.e. a tangent vector). In common usage the former is called the differential of the function and the latter is called the gradient. Gumshoe2 (talk) 15:55, 29 January 2024 (UTC)[reply]

Example of vector which is not contravariant is arguably not a vector

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Currently: "On the other hand, for instance, a triple consisting of the length, width, and height of a rectangular box could make up the three components of an abstract vector, but this vector would not be contravariant, since a change in coordinates on the space does not change the box's length, width, and height: instead these are scalars." I think this is not helpful since there is no obvious meaning to the vector space of box [length, width, height]. What do vector scaling and vector addition correspond to? I suggest this example be removed. Intellec7 (talk) 05:19, 28 August 2020 (UTC)[reply]

OK. Go ahead and delete that sentence. JRSpriggs (talk) 14:47, 28 August 2020 (UTC)[reply]

Geometrical construction of coordinates

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If you have a basis in a three dimensional Euclidean space you can construct the coordinates of a given point by drawing lines through the point parallel to each basis vector. Those lines will intersect with each other and the distance of the intersection point from the origin divided by the length of the corresponding basis vector gives you the covariant components . But how do you construct the coordinates in respect to the dual basis  ???? 2003:E7:2F3B:B0D8:11C:4108:841E:BA24 (talk) 07:00, 17 April 2021 (UTC)[reply]

Mis-use of the word "scalar"

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The word "scalar" is used in the page to mean something that multiplies a unit vector. But a scalar is supposed to be coordinate-free or gauge-invariant or invariant to changes of coordinates. The quantities that multiply unit vectors do not have this property, because the unit vectors change (and hence the components of the vectors change) as you change coordinates. --David W. Hogg (talk) 12:58, 16 May 2021 (UTC)[reply]

I tried to fix that. Let me know if there is still a problem. JRSpriggs (talk) 18:26, 16 May 2021 (UTC)[reply]
What about scalar densities (or if you refer to work from a concrete example, 'density' as in kg/m^3)? These are rank-zero tensors (or tensor fields) but nevertheless they are covariant. Can't recall the name, but one text I have read suggests that you can also have a 'scalar capacity', which can also be a field, which is a contravariant scalar. — Preceding unsigned comment added by 203.13.3.89 (talk) 03:26, 29 January 2024 (UTC)[reply]

Vectors vs. Covectors

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I have some "issues" with the fundamental jargon used in this article. I would like to help improve it; but I don't want to start an editing war. So, let me test the waters with a few comments:

Vectors and covectors are not the same thing. And they are both invariant under (proper, invertible) linear transformation. (Note: this is the passive/alias viewpoint of transformations). It is a semantic error to say that a vector is contravariant (or that a covector is covariant). The co/vectors, and tensors in general, are invariant under linear transformations. If the space has a metric, then one can "convert" a vector into a covector, and vice versa. But the existence of a metric is not obligatory and, in fact, confuses people into thinking that vectors and covectors are fungible. They are not. Vectors are linear approximations to the curves defined by the intersection of coordinate functions; covectors are linear functional approximations to the level (hyper)surfaces of a single coordinate function. The figure at the top of the article kind of hints at this, but then garbles the message by overlaying arrow quantities with level-surface quantities on the right-hand side. Too bad. Remove those blue arrows and you'd have a right proud representation of covectors in a cobasis.

Co/contra-variance is a property of the components and of the basis elements. For a vector , the components are contravariant and the basis vectors are covariant; for a covector , the components are covariant and the basis covectors are contravariant. In either case, when you contract the components with the basis—one of which is covariant and the other contravariant—then you get an invariant quantity, as required of a tensor.

I won't try to define/defend here (yet;-) what co/contra-variant mean. (Spoiler alert: contravariant quantities transform as the Jacobian of a coordinate transformation; covariant quantities transform as the inverse Jacobian; this seems backwards to what I, for one, would expect from the concepts of co- and contra-; but it is what it is!)

To whomever has purview over this article: if these comments make sense and seem worth the trouble of editing the article, please let me know and I'll try to collaborate. On the other hand, if you think these are distinctions without a difference—or worse, misguided—then I'll stand down.--ScriboErgoSum (talk) 08:25, 15 November 2021 (UTC)[reply]

NPOV

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The article describes covariance and contravariance in terms of coordinates and components, a perspective that is rather dated. The terms have a meaning independent of any choice of basis or coordinates, and the article should reflect that. There is a lot of variation in the literature, but essentially there are three styles:

  1. Define the tangent and cotangent bundles independently, then prove duality.
    1. Authors often define tangent vectors as equivalence classes of curves through a point.
    2. Authors often define cotangent vectors in the language of germs.
  2. Define the tangent bundle, define the cotangent space at a point as the dual of the tangent space at that point and then define the cotangent bundle.
  3. Define the cotangent bundle, define the tangent space at a point as the dual of the cotangent space at that point and then define the tangent bundle.

Tensors can then be defined as either tensor products or as multilinear maps. It is common to just classify tensors by the covariant and contravariant ranks, but if there is a (pseudo)metric involved then order matters because of raising and lowering of indexes. --Shmuel (Seymour J.) Metz Username:Chatul (talk) 11:32, 1 March 2022 (UTC)[reply]

This article mostly describes tensors; what you are describing is tensor field. But taking your point, there should be some section for the tensor product language on this page. Even so, there is no need to choose one way over another. (I object to the idea that bases and coordinates are dated.) Gumshoe2 (talk) 07:26, 13 March 2022 (UTC)[reply]
There is a large amount of material in the Tensors article that does not belong there, but should rather be in Tensor fields. The distinction between covariant and contravariant is really only relevant for tensor fields on a manifold, but as long as it is in this article the text should reflect its character.
I didn't say that coordinates and bases are dated, but rather that defining, e.g., tensor, covariant, in terms of coordinates and bases rather than intrinsically is dated. --Shmuel (Seymour J.) Metz Username:Chatul (talk) 12:51, 13 March 2022 (UTC)[reply]
I agree that the tensor product definition should be given here, but I think it should be given together with the present one. Why do you say that co(/ntra)variance is only relevant for tensor fields? There is of course a distinction between an element of a vector space and an element of the dual vector space, for instance. Gumshoe2 (talk) 17:37, 13 March 2022 (UTC)[reply]
Whoops! Yes, of course there is a difference between V and V* for an abstract vector space V, not just for tangent spaces. --Shmuel (Seymour J.) Metz Username:Chatul (talk) 19:21, 13 March 2022 (UTC)[reply]

Inconsistency of note 1 with the main text

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I am adding this (3/26/2022) without reading the below because I have a comment on the definition section. We have f = (X1, ..., Xn) with each of the Xis being basis a vector. I was going to add a remark that said this makes f a matrix and indeed it is used as a matrix in the unnumbered equation v=f v[f]. I decided not to add that comment as it contradicts Note 1. In the note preceding Eq 1 it says "regarding f as a row vector whose entries are the elements of the basis". Maybe I am naive but I find this pretty confusing as I've always considered matrices and vectors to be different objects. If f is to be considered a row vector but with each element a basis vector instead of just a number (as one usually thinks of vectors) this needs to be explained. If the note is incorrect then it should be removed. — Preceding unsigned comment added by 76.113.29.12 (talkcontribs) 14:45, 26 March 2022 (UTC)[reply]

I removed the template. It is sometimes useful when dealing with matrices to consider a matrix as a column vector of row vectors or a row vector of column vectors. In this sense, a vector is just a list of some object even though it's entries are not strictly from a field. I tend to agree with your level of scrutiny, which if applied would require we don't use the word vector (see here). The wording of vector could be changed to that of list, but I don't think that would be a helpful change and actually could be a little detrimental, so I am leaving it. 69.166.46.156 (talk) 19:35, 25 April 2022 (UTC)[reply]

Relative vectors?

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Should the article discuss relative vectors, whose transformation includes a power of the transformation determinant as a factor? In more modern language, these are tensor products of vectors with tensor densities, or for orientable manifolds, liftings of line bundles. -- Shmuel (Seymour J.) Metz Username:Chatul (talk) 14:31, 13 November 2023 (UTC)[reply]

This seems like a good place for it. Note that in tensor there is some content on tensor densities which uses notation compatible with this article. Tito Omburo (talk) 22:31, 15 March 2024 (UTC)[reply]

Orthogonal is not enough

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@JRSpriggs: In permalink/1233199815 I changed in 3-d general curvilinear coordinates (q1, q2, q3), a tuple of numbers to define a point in a position space. Note the basis and cobasis coincide only when the basis is orthogonal to in 3-d general curvilinear coordinates (q1, q2, q3), a tuple of numbers to define a point in a position space. Note the basis and cobasis coincide only when the basis is orthonormall. In permalink/1233348907, JRSpriggs reverted to the to last version by Derek farn, undoing edits by 76.116.252.35, me and Antoni Parellada . Orthogonality ia not a strong enough condition for the basis and cobasis to coincide; they have to be both orthogonal and of norm 1, i.e., orthonormal. -- Shmuel (Seymour J.) Metz Username:Chatul (talk) 14:33, 12 July 2024 (UTC)[reply]

I agree it should be orthonormal. It seems the erroneous statement has been there unchallenged since 09:11, 3 September 2012, with a reference to a reliable source (but no page number). I don't have a copy of that book, so I can't tell if it's been misinterpreted and I don't have to hand a reliable source of my own. @Chatul, do you have a reliable source for this? By the way, the orthonormality is already mentioned in the article, in the last sentence of the "Three-dimensional Euclidean space" subsection.  Dr Greg  talk  17:52, 12 July 2024 (UTC)[reply]
I corrected it and added {{specify}}. MTW is an unimpeachable source, but a quick search in my dead tree version turned up nothing relevant; I'll check the index for dual basis and Tetrad.
I was tempted to add a {{cn}} to § Three-dimensional Euclidean space but thought BLUESKY might apply. -- Shmuel (Seymour J.) Metz Username:Chatul (talk) 06:53, 14 July 2024 (UTC)[reply]